Legalizing Artificial Intelligence

Georgios I. Zekos
Additional contact information
Georgios I. Zekos: International Hellenic University

Chapter Chapter 9 in Economics and Law of Artificial Intelligence, 2021, pp 361-400 from Springer

Abstract: Abstract Current boardroom technologies concentrate on the production and distribution of information that boards want to assist in their supervisory and strategic roles which mean that many of these technologies do not tender the advantages of AI systems themselves but instead engender the data which is the necessary lifeblood that AI needs. Advanced analytics based on AI algorithms categorize more complex patterns than is possible by human intervention, predominantly in the context of identifying fraud and money laundering in the financial services context. AI can be considered as property and so making the obligation of the clients, owners, or producers if the damage is caused because of it. The European Parliament passed a resolution proposing a form of legal personhood for Artificial Intelligence regardless that legal personality is not lightly conferred in any jurisdiction. As AI entities function at an increasing distance from their developers and owners, these AI entities confront conventional legal frameworks for attribution and liability. This author (Georgios I Zekos) considers that there is a need for attributing legal personhood to AI entities, in their present configuration, in an analogous way that of traditional corporations and the only difference is that of their virtual dimension of function because humans are creating AI entities and put them in operation and so the occurrence of AI entities put in function by other AI entities is for the future where it is supposed to have a legal personhood attributing liability for the original AI entities and be forced in an AI way by AI entities in an AI world.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-64254-9_9

Ordering information: This item can be ordered from
http://www.springer.com/9783030642549

DOI: 10.1007/978-3-030-64254-9_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().